A live cell imaging method and device based on holographic microscopy

Abstract

The present invention discloses a live cell imaging method and device based on holographic microscopy. A live cell imaging method based on holographic microscopy includes: placing a live cell sample on a three-dimensional micron-level displacement platform to control the spatial position of the live cell sample; splitting a laser light source into a reference beam and a sample beam; focusing the sample beam on the live cell sample through a microscope, and then reaching a holographic detector through an optical element to interfere with the reference beam to generate a holographic image; reconstructing the holographic image to obtain a three-dimensional image of the live cell sample; the present invention obtains an initial optimal path of the sample beam and the reference light speed on the holographic detector based on a population algorithm, minimizing the optical path difference, thereby improving the overall imaging quality. At the same time, the holographic image is reconstructed through phase retrieval, so that the final three-dimensional image has higher resolution and better dynamic tracking ability.

Description

Technical Field

[0001] The present invention relates to the technical field of cell imaging, and in particular, to a method and device for live cell imaging based on holographic microscopy. Background Art

[0002] Holographic microscopy is a high-resolution imaging technology based on the principles of interference and diffraction, and is widely used in the biomedical field to facilitate the observation of small and complex biological samples. Holographic microscopy was first proposed by physicist Dennis Gabor in the 1940s and has since been developed and optimized. By recording and analyzing the interference pattern between the sample and the reference beam, this technology can generate high-resolution images without physically cutting or chemically staining the sample, thus achieving precise imaging without damaging the sample. The development of holographic microscopy has evolved from early optical holography to modern digital holography and computational holographic microscopy techniques.

[0003] Traditional holographic microscopy often uses a single-channel interference image recording method. Although it has significant advantages in observing the internal structure of cells, it is still limited in terms of spatial resolution and imaging depth. To overcome these deficiencies, researchers have gradually introduced multi-beam interference technology and digital holography technology. These technological advancements have enabled holographic microscopy to achieve higher-precision and deeper three-dimensional imaging. However, the existing technology still faces many challenges in processing dynamic cell imaging, such as the difficulty of real-time imaging and the often difficult to achieve micron-level precise control when dealing with the three-dimensional spatial distribution of samples. Summary of the Invention

[0004] To overcome the above defects in the prior art, the present invention provides a method for live cell imaging based on holographic microscopy, including: placing a live cell sample on a three-dimensional micron-level displacement platform and controlling the spatial position of the live cell sample; splitting a laser light source into a reference beam and a sample beam; the sample beam is focused on the live cell sample through a microscope and then reaches a holographic detector through an optical element, where it interferes with the reference beam to generate a holographic image; reconstructing the holographic image to obtain a three-dimensional image of the live cell sample.

[0005] As a preferred embodiment of the method for live cell imaging based on holographic microscopy of the present invention, it includes: emitting a laser light source through a semiconductor laser, and the coherence length L of the laser light source is:

[0006] L = 2FWHM / π

[0007] where FWHM is the full width at half maximum of the laser spectrum;

[0008] The laser light source is split into a reference beam and a sample beam by a beam splitter, and the transmittance T and reflectance R of the beam splitter are as follows:

[0009] T = I s / I i ;

[0010] R = I r / I i

[0011] wherein, I s is the light intensity entering the live cell sample, I i is the total light intensity incident on the beam splitter, and I r is the light intensity entering the reference beam.

[0012] As a preferred embodiment of the live cell imaging method based on holographic microscopy according to the present invention, it includes: respectively calculating the initial paths of the sample beam and the reference light speed on the holographic detector; respectively defining a first objective function F1 and a second objective function F2 according to the initial paths; randomly generating the positions of the whale population, and each position represents optical parameters; calculating the fitness of the whale individuals; updating the positions of the whale individuals, calculating the fitness of the whale individuals at this time, and selecting the one with the minimum fitness as the optimal individual.

[0013] As a preferred embodiment of the live cell imaging method based on holographic microscopy according to the present invention, it includes: the pixel size dpixel of the holographic detector satisfies the following conditions:

[0014] dpixel ≤ λ / (2·NA)

[0015] wherein, NA is the numerical aperture.

[0016] As a preferred embodiment of the live cell imaging method based on holographic microscopy according to the present invention, the reconstruction includes: performing filtering processing on the holographic image; performing weighted fusion on the holographic images at different angles; performing multi-scale analysis processing on the fused holographic image, decomposing the fused holographic image into components at different scales, and processing layer by layer from low scale to high scale to capture the details at each level; randomly setting an initial phase estimate, combining the amplitude information of the holographic image and the phase information of the reference beam, and repeatedly iterating to optimize the phase estimate, and outputting a three-dimensional image after the iteration ends.

[0017] As a preferred embodiment of the live cell imaging device based on holographic microscopy according to the present invention, it includes: a position control module configured to place a live cell sample on a three-dimensional micrometer-scale displacement platform and control the spatial position of the live cell sample; a laser light source module configured to split a laser light source into a reference beam and a sample beam; a holographic imaging module configured to focus the sample beam on the live cell sample through a microscope and then reach a holographic detector through an optical element to interfere with the reference beam to generate a holographic image; and an image reconstruction module configured to reconstruct the holographic image to obtain a three-dimensional image of the live cell sample.

[0018] As a preferred embodiment of the live cell imaging device based on holographic microscopy according to the present invention, the laser light source module is specifically configured to: emit a laser light source through a semiconductor laser, and the coherence length L of the laser light source is:

[0019] L = 2FWHM / π

[0020] where FWHM is the full width at half maximum of the laser spectrum;

[0021] split the laser light source into a reference beam and a sample beam through a beam splitter, and the transmittance T and reflectivity R of the beam splitter are:

[0022] T = I s / I i ;

[0023] R = I r / I i

[0024] where I s is the light intensity entering the live cell sample, I i is the total light intensity incident on the beam splitter, and I r is the light intensity entering the reference beam.

[0025] As a preferred embodiment of the live cell imaging device based on holographic microscopy according to the present invention, the holographic imaging module is specifically configured to: calculate the initial paths of the sample beam and the reference light beam on the holographic detector respectively; define a first objective function F1 and a second objective function F2 according to the initial paths respectively; randomly generate the positions of the whale population, and each position represents an optical parameter; calculate the fitness of the whale individuals; update the positions of the whale individuals, calculate the fitness of the whale individuals at this time, and select the one with the minimum fitness as the optimal individual.

[0026] As a preferred embodiment of the live cell imaging device based on holographic microscopy according to the present invention, the pixel size dpixel of the holographic detector satisfies the following conditions:

[0027] dpixel ≤ λ / (2·NA)

[0028] Wherein, NA is the numerical aperture.

[0029] As a preferred solution of the live cell imaging device based on holographic microscopy according to the present invention, wherein: The image reconstruction module is specifically configured to perform: filtering the holographic image; weighted fusion of holographic images at different angles; multi-scale analysis processing of the fused holographic image, decomposing the fused holographic image into components of different scales, and processing layer by layer from low scale to high scale to capture details at each level; randomly setting an initial phase estimate, combining the amplitude information of the holographic image and the phase information of the reference beam, and iterating repeatedly to optimize the phase estimate, and outputting a three-dimensional image after the iteration ends.

[0030] Advantages of the present invention: The present invention obtains the initial path of the optimal path of the sample beam and the reference light speed on the holographic detector based on the swarm algorithm, minimizes the optical path difference, thereby improving the overall imaging quality. At the same time, the holographic image is reconstructed by phase recovery, so that the final three-dimensional image has higher resolution and better dynamic tracking ability. Description of the Drawings

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. Among them:

[0032] Figure 1 It is a schematic flowchart of the live cell imaging method based on holographic microscopy according to the first embodiment of the present invention;

[0033] Figure 2 It is a schematic flowchart of reconstructing the holographic image according to the first embodiment of the present invention. Detailed Embodiments

[0034] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the detailed embodiments of the present invention with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the spirit of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0036] Secondly, as used herein, an "embodiment" or "embodiments" refers to specific features, structures, or characteristics that may be included in at least one implementation of the present invention. The phrase "in an embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments.

[0037] The present invention will be described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the cross-sectional views showing the device structure will be enlarged locally out of the general scale, and the schematic diagrams are only examples and should not limit the scope of protection of the present invention herein. In addition, in actual production, three-dimensional spatial dimensions including length, width, and depth should be included.

[0038] Meanwhile, in the description of the present invention, it should be noted that the orientation or positional relationships indicated by terms such as "upper, lower, inner, and outer" are based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention. In addition, the terms "first, second, or third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0039] Unless otherwise clearly defined and limited in the present invention, the terms "mounted, connected, and coupled" shall be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may also be a mechanical connection, an electrical connection, or a direct connection, or may be indirectly connected through an intermediate medium, or may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0040] Embodiment 1

[0041] Referring to Figures 1 to 2 , which is the first embodiment of the present invention, this embodiment provides a live cell imaging method based on holographic microscopy, including:

[0042] S1: Place the live cell sample on a three-dimensional micron-scale displacement platform and control the spatial position of the live cell sample.

[0043] The three-dimensional micron-scale displacement platform can perform micron-scale precise displacement in three dimensions to facilitate the fine positioning and scanning of live cell samples (such as cancer cells, bacteria).

[0044] S2: Divide the laser light source into a reference beam and a sample beam.

[0045] Emit a laser light source through a semiconductor laser. The coherence length L (the distance over which the laser light source maintains coherence) of the laser light source is:

[0046] L = 2FWHM / π

[0047] In the formula, FWHM is the full width at half maximum of the laser spectrum;

[0048] Divide the laser light source into a reference beam and a sample beam through a beam splitter. The transmittance T and reflectivity R of the beam splitter are:

[0049] T = I s / I i ;

[0050] R = I r / I i

[0051] In the formula, I s is the light intensity entering the live cell sample, I i is the total light intensity incident on the beam splitter, and I r is the light intensity entering the reference beam.

[0052] S3: The sample beam is focused on the live cell sample through a microscope, and then reaches the holographic detector through an optical element, where it interferes with the reference beam to generate a holographic image.

[0053] The numerical aperture NA of the microscope objective is greater than 0.8, and the resolution is:

[0054] Resolution = 1.22·λ / NA

[0055] The sample beam is focused on the live cell sample through a microscope, and then reaches the holographic detector through an optical element (lens or mirror), where it meets and interferes with the reference beam on the holographic detector to generate a holographic image.

[0056] Among them, in this embodiment, the polymer photonic crystal is fixed on the surface or inside of the beam splitter lens through thin film deposition, interlayer bonding or inlay technology, so as to achieve higher imaging resolution; the lattice structure of the polymer photonic crystal is a body-centered cubic (BCC) structure, the lattice constant (a) is 600 nm, and each unit cell contains four spherical holes with a pore diameter (r) of 200 nm (the radius of the hole).

[0057] The mirror includes a high refractive index layer and a low refractive index layer, and the materials of the high refractive index layer and the low refractive index layer are silicon and air respectively; the high refractive index layer and the low refractive index layer are alternately stacked, and the thickness of each layer is 1 / 6 of the optical wavelength to achieve enhanced reflection of light by optical interference. The thickness of each high refractive index layer is λ / 4n, where λ is the designed wavelength and n is the refractive index of silicon; the thickness of each low refractive index layer is λ / 4n; the total number of layers of the mirror is 20, and the thickness of each layer is precisely controlled to ensure complete reflection of light within the target wavelength range. Preferably, the mirror designed in this embodiment utilizes the interference effect of light to achieve high reflectivity at a specific wavelength, and by setting the thickness of each layer to a quarter wavelength of the designed wavelength, it ensures that the mirror has strong reflection ability within this wavelength range.

[0058] Preferably, high-quality lenses and mirrors are used to guide the sample beam and the reference beam to ensure minimal light loss and distortion.

[0059] The pixel size dpixel of the holographic detector satisfies the following condition:

[0060] dpixel ≤ λ / (2·NA)

[0061] In the formula, NA is the numerical aperture.

[0062] Furthermore, the initial paths L1 and L2 of the sample beam and the reference light beam on the holographic detector are calculated respectively, and the optimal path is obtained by combining with the optimized whale algorithm to minimize the optical path difference, thereby improving the overall imaging quality. Specifically:

[0063] (1) Optimize the path of the sample beam on the holographic detector

[0064] ① Define the first objective function F1 according to the initial path L1 of the sample beam on the holographic detector:

[0065]

[0066] In the formula, NA i is the numerical aperture of the i-th optical element (Numerical Aperture). The larger the numerical aperture, the better the focusing performance of the beam, and the smaller the scattering and diffraction losses of light; L distance is the distance between optical elements.

[0067] ② Randomly generate the positions of the whale population, and each position represents the optical parameters, that is, the numerical aperture of the optical element.

[0068] ③ Calculate the fitness of the whale individuals, that is, the objective function value of the whale individuals.

[0069] ④ Update the positions of the whale individuals, calculate the fitness of the whale individuals at this time, and select the one with the smallest fitness as the optimal individual.

[0070] X new = X best - C·|B·X best - X|

[0071] In the formula, X new is the new position, X best is the position of the current optimal solution, X is the position of the current whale, C is the scaling factor, which controls the movement range of the whale, and its value range is [0, 1], and B is the coefficient that affects the movement of the whale, and its value range is [0, 1].

[0072] Furthermore, the scaling factor is dynamically adjusted during the iteration process:

[0073] C(t) = C0·exp(-βt)

[0074] In the formula, C(t) is the scaling factor in the t-th iteration, C0 is the initial value of the scaling factor, and β is the parameter that controls the attenuation rate.

[0075] (2) Optimize the path of the reference beam on the holographic detector

[0076] ① Define the first objective function F2 according to the initial path L1 of the sample beam on the holographic detector:

[0077]

[0078] In the formula, (x1, y1, z1) are the starting point coordinates of the reference beam, and (x2, y2, z2) are the ending point coordinates of the reference beam.

[0079] ② Randomly generate the positions of the whale population, and each position represents the optical parameters, that is, the reference beam path coordinates.

[0080] ③ Calculate the fitness of the whale individuals, that is, the objective function value of the whale individuals.

[0081] ④ Update the positions of the whale individuals, calculate the fitness of the whale individuals at this time, and select the one with the minimum fitness as the optimal individual.

[0082] X new = X best - C·|B·X best - X|

[0083] In the formula, X new is the new position, X bestis the position of the current optimal solution, X is the position of the current whale, C is the scaling factor, which controls the movement range of the whale and takes values in the range [0, 1], and B is the coefficient that affects the movement of the whale, taking values in the range [0, 1].

[0084] Furthermore, the scaling factor is dynamically adjusted during the iteration process:

[0085] C(t) = C0·exp(-βt)

[0086] In the formula, C(t) is the scaling factor in the t-th iteration, C0 is the initial value of the scaling factor, and β is the parameter that controls the attenuation rate.

[0087] Preferably, the beam path is optimized by combining the optimized whale algorithm, ensuring the shortest and straightest optical path to reduce the distortion of the interference pattern.

[0088] S4: Reconstruct the holographic image to obtain a three-dimensional image of the living cell sample.

[0089] Refer to Figure 2 , and filter the holographic image through the adaptive median filtering algorithm; specifically, calculate the local statistical characteristics of the image (i.e., the standard deviation of the noise), and dynamically adjust the window size and weight of the filter to remove unnecessary noise while retaining the edge information, providing clearer input data for subsequent reconstruction;

[0090] Weightedly fuse the holographic images at different angles. Specifically, weightedly fuse the holographic images at each perspective, and the weights are determined according to the clarity and contrast of the holographic images, thereby improving the overall quality of the image and reducing the image differences caused by different perspectives.

[0091] Perform multi-scale analysis processing on the fused holographic image. Specifically, perform wavelet transform on the fused holographic image, decompose the fused holographic image into components at different scales, and process layer by layer from low scale to high scale to capture the details at each level; the holographic image at each scale undergoes filtering and preliminary reconstruction, and finally the results at each scale are fused.

[0092] Furthermore, randomly set the initial phase estimation (the phase can be set to zero or generate a randomly distributed phase image with a uniform distribution), and determine the size and resolution of the holographic image to ensure matching with the actual data.

[0093] Combining the amplitude information of the holographic image and the phase information of the reference beam, iterating repeatedly to optimize the phase estimation, and outputting a three-dimensional image after the iteration ends. Specifically, applying the current phase estimation and amplitude information to the Fourier transform to obtain a frequency-domain representation. In the frequency domain, using the current phase estimation to calculate the complex amplitude of the holographic image. Combining the amplitude information of the actual holographic image with the amplitude information in the frequency-domain representation, keeping the amplitude of the holographic image-like unchanged. Further, performing an inverse Fourier transform on the updated frequency-domain data to obtain an updated spatial-domain image. Updating the phase information in the image after the inverse Fourier transform to the current estimation, and the obtained updated phase information will be used to generate the input for the next round of iteration. Repeating the above processes of Fourier transform, amplitude combination, and phase update until the algorithm reaches the convergence condition, and outputting a three-dimensional image.

[0094] The convergence condition is: terminate after reaching the preset maximum number of iterations, and the maximum number of iterations is 100 times.

[0095] Example 2

[0096] What is different from the first embodiment in this embodiment is that a live cell imaging device based on holographic microscopy is provided, including,

[0097] A position control module, configured to place a live cell sample on a three-dimensional micrometer-level displacement platform and control the spatial position of the live cell sample;

[0098] A laser light source module, configured to split a laser light source into a reference beam and a sample beam;

[0099] A holographic imaging module, configured to focus the sample beam on the live cell sample through a microscope, and then reach a holographic detector through an optical element, interfere with the reference beam, and generate a holographic image;

[0100] An image reconstruction module, configured to reconstruct the holographic image to obtain a three-dimensional image of the live cell sample.

[0101] Among them, the laser light source module is specifically configured to perform:

[0102] Emitting a laser light source through a semiconductor laser, and the coherence length L of the laser light source is:

[0103] L = 2FWHM / π

[0104] In the formula, FWHM is the full width at half maximum of the laser spectrum;

[0105] Splitting the laser light source into a reference beam and a sample beam through a beam splitter, and the transmittance T and reflectivity R of the beam splitter are:

[0106] T = I s / I i;

[0107] R = I r / I i

[0108] In the formula, I s is the light intensity entering the live cell sample, and I i is the total light intensity incident on the beam splitter, and I r is the light intensity entering the reference beam.

[0109] Among them, the holographic imaging module is specifically configured to perform:

[0110] Calculate the initial paths of the sample beam and the reference light speed on the holographic detector respectively;

[0111] Define the first objective function F1 and the second objective function F2 according to the initial paths respectively;

[0112] Randomly generate the positions of the whale population, and each position represents optical parameters;

[0113] Calculate the fitness of the whale individuals;

[0114] Update the positions of the whale individuals, calculate the fitness of the whale individuals at this time, and select the one with the minimum fitness as the optimal individual.

[0115] The pixel size dpixel of the holographic detector satisfies the following conditions:

[0116] dpixel ≤ λ / (2·NA)

[0117] In the formula, NA is the numerical aperture.

[0118] Among them, the image reconstruction module is specifically configured to perform:

[0119] Perform filtering processing on the holographic image;

[0120] Perform weighted fusion on the holographic images at different angles;

[0121] Perform multi-scale analysis processing on the fused holographic image, decompose the fused holographic image into components at different scales, and process layer by layer from low scale to high scale to capture the details at each level;

[0122] Randomly set the initial phase estimation, combine the amplitude information of the holographic image and the phase information of the reference beam, and iterate repeatedly to optimize the phase estimation. After the iteration ends, output a three-dimensional image.

[0123] It should be recognized that embodiments of the present invention can be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The methods can be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes a computer to operate in a specific and predefined manner - in accordance with the methods and figures described in the specific embodiments. Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. Additionally, for this purpose the program is capable of running on a programmed application-specific integrated circuit.

[0124] In addition, the operations of the processes described herein can be performed in any suitable order, unless otherwise indicated herein or otherwise clearly contradicted by the context. The processes described herein (or variations and / or combinations thereof) can be performed under the control of one or more computer systems configured with executable instructions, and can be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or by a combination thereof. The computer programs include a plurality of instructions executable by one or more processors.

[0125] Further, the methods can be implemented in any type of computing platform operably connected, including but not limited to personal computers, minicomputers, mainframes, workstations, network or distributed computing environments, standalone or integrated computer platforms, or communicating with charged particle tools or other imaging devices, etc. Aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into the computing platform, such as a hard disk, optical read and / or write storage medium, RAM, ROM, etc., such that it can be read by a programmable computer and, when read by the storage medium or device, can be used to configure and operate the computer to perform the processes described herein. Additionally, the machine-readable code, or portions thereof, can be transmitted via a wired or wireless network. When such media include instructions or programs that implement the above-described steps in conjunction with a microprocessor or other data processor, the inventions described herein include these and other different types of non-transitory computer-readable storage media. When programmed in accordance with the methods and techniques of the present invention, the present invention also includes the computer itself. The computer program is capable of applying to input data to perform the functions described herein, thereby transforming the input data to generate output data stored in non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the transformed data represents physical and tangible objects, including a specific visual depiction of the physical and tangible objects generated on a display.

[0126] As used in this application, the terms "component", "module", "system", etc. are intended to refer to computer-related entities, which can be hardware, firmware, a combination of hardware and software, software, or software in operation. For example, a component can be, but is not limited to: a process running on a processor, a processor, an object, an executable file, a thread in execution, a program, and / or a computer. As an example, an application running on a computing device and the computing device can both be components. One or more components can exist in a process and / or thread in execution, and a component can be located in one computer and / or distributed between two or more computers. In addition, these components can execute from various computer-readable media having various data structures thereon. These components can communicate in a local and / or remote procedure manner through signals such as signals having one or more data packets (e.g., data from one component that interacts with another component in a local system, a distributed system, and / or communicates with other systems via a network such as the Internet in a signal manner).

[0127] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A live cell imaging method based on holographic microscopy, characterized in that, Including: Placing a live cell sample on a three-dimensional micrometer-level displacement platform to control the spatial position of the live cell sample; Dividing a laser light source into a reference beam and a sample beam; The sample beam is focused on the live cell sample through a microscope, and then reaches a holographic detector through an optical element, interfering with the reference beam to generate a holographic image; Reconstructing the holographic image to obtain a three-dimensional image of the live cell sample; Wherein, during the process of generating the holographic image, the initial paths L1 and L2 of the sample beam and the reference beam on the holographic detector are respectively calculated, and the optimal path is obtained by combining an optimized whale algorithm to minimize the optical path difference. Specifically: Respectively calculate the initial paths of the sample beam and the reference light beam on the holographic detector; Define a first objective function F1 and a second objective function F2 according to the initial paths; Randomly generate the positions of the whale population, and each position represents an optical parameter; Calculate the fitness of the whale individuals; Update the positions of the whale individuals, calculate the fitness of the whale individuals at this time, and select the one with the minimum fitness as the optimal individual; Wherein, the first objective function F1 is defined as: Wherein, NA i is the numerical aperture of the i-th optical element. The larger the numerical aperture, the better the focusing performance of the light beam, and the smaller the scattering and diffraction losses of light; L distance is the distance between optical elements; The second objective function F2 is defined as: In the formula, (x1, y1, z1) are the starting point coordinates of the reference beam, and (x2, y2, z2) are the ending point coordinates of the reference beam; The formula for updating the positions of the whale individuals is specifically: X new = X best - C · |B · X best - X|; where X new is the new position, X best is the position of the current optimal solution, X is the position of the current whale, C is the scaling factor that controls the movement range of the whale, and its value range is [0, 1], and B is the coefficient that affects the movement of the whale, and its value range is [0, 1].

2. The live cell imaging method based on holographic microscopy according to claim 1, characterized in that, Including: Emitting a laser light source through a semiconductor laser, and the coherence length L of the laser light source is: L = 2FWHM / π In the formula, FWHM is the full width at half maximum of the laser spectrum; Dividing the laser light source into a reference beam and a sample beam through a beam splitter, and the transmittance T and reflectivity R of the beam splitter are: T = I s / I i ; R = I r / I i Where, I s is the light intensity entering the live cell sample, I i is the total light intensity incident on the beam splitter, and I r is the light intensity entering the reference beam.

3. The live cell imaging method based on holographic microscopy according to claim 2, wherein, Including: The pixel size dpixel of the holographic detector satisfies the following conditions: dpixel ≤ λ / (2·NA) In the formula, NA is the numerical aperture.

4. The live cell imaging method based on holographic microscopy according to claim 3, wherein, The reconstruction includes: Performing filtering processing on the holographic image; Performing weighted fusion on the holographic images at different angles; Performing multi-scale analysis processing on the fused holographic image, decomposing the fused holographic image into components at different scales, and processing layer by layer from low scale to high scale to capture the details at each level; Randomly setting an initial phase estimate, combining the amplitude information of the holographic image and the phase information of the reference beam, and iterating repeatedly to optimize the phase estimate, and outputting a three-dimensional image after the iteration ends.

5. A live cell imaging device based on holographic microscopy, characterized in that, Including: A position control module configured to place a live cell sample on a three-dimensional micrometer-level displacement platform and control the spatial position of the live cell sample; A laser light source module configured to divide a laser light source into a reference beam and a sample beam; A holographic imaging module configured to focus the sample beam on the live cell sample through a microscope, and then reach a holographic detector through an optical element, interfering with the reference beam to generate a holographic image; An image reconstruction module configured to reconstruct the holographic image to obtain a three-dimensional image of the live cell sample; Wherein, the holographic imaging module is specifically configured to perform: Respectively calculate the initial paths of the sample beam and the reference beam on the holographic detector; Define a first objective function F1 and a second objective function F2 according to the initial paths; Randomly generate the positions of the whale population, where each position represents optical parameters; Calculate the fitness of each whale individual; Update the positions of the whale individuals, calculate the fitness of the whale individuals at this time, and select the one with the minimum fitness as the optimal individual; Among them, the first objective function F1 is defined as: Wherein, NA i is the numerical aperture of the i-th optical element. The larger the numerical aperture, the better the focusing performance of the light beam, and the smaller the scattering and diffraction losses of the light; L distance is the distance between the optical elements; The second objective function F2 is defined as: In the formula, (x1, y1, z1) are the starting point coordinates of the reference beam, and (x2, y2, z2) are the ending point coordinates of the reference beam; The formula for updating the positions of the whale individuals is specifically: X new = X best - C · |B · X best - X|; where X new is the new position, X best is the position of the current optimal solution, X is the position of the current whale, C is the scaling factor that controls the movement range of the whale, and its value range is [0, 1], and B is the coefficient that affects the movement of the whale, and its value range is [0, 1].

6. The live cell imaging device based on holographic microscopy according to claim 5, characterized in that, The laser light source module is specifically configured to execute: Emit a laser light source through a semiconductor laser, and the coherence length L of the laser light source is: L = 2FWHM / π In the formula, FWHM is the full width at half maximum of the laser spectrum; Divide the laser light source into a reference beam and a sample beam through a beam splitter, and the transmittance T and reflectivity R of the beam splitter are: T = I s / I i ; R = I r / I i Where, I s is the light intensity entering the live cell sample, I i is the total light intensity incident on the beam splitter, and I r is the light intensity entering the reference beam.

7. The live cell imaging device based on holographic microscopy according to claim 6, characterized in that, The holographic imaging module is specifically configured to execute: The pixel size dpixel of the holographic detector satisfies the following conditions: dpixel ≤ λ / (2·NA) In the formula, NA is the numerical aperture.

8. The live cell imaging device based on holographic microscopy according to claim 7, wherein, The image reconstruction module is specifically configured to execute: Perform filtering processing on the holographic image; Perform weighted fusion on the holographic images at different angles; Perform multi-scale analysis processing on the fused holographic image, decompose the fused holographic image into components of different scales, and process layer by layer from low scale to high scale to capture the details at each level; Randomly set the initial phase estimation, combine the amplitude information of the holographic image and the phase information of the reference beam, and iterate repeatedly to optimize the phase estimation. After the iteration ends, output a three-dimensional image.

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